Identify and classify duplicate TCR records in VDJdb databases using Python.
npx skills add https://github.com/antigenomics/vdjdb-db --skill vdjdb-duplicates
Please help me install this Agent Skill. Skill: vdjdb-duplicates Source: https://github.com/antigenomics/vdjdb-db/tree/main/skills/vdjdb-duplicates Command: npx skills add https://github.com/antigenomics/vdjdb-db --skill vdjdb-duplicates
This Skill identifies and classifies duplicate TCR records in the VDJdb database, ensuring data consistency and accuracy.
Run the skill by executing /vdjdb-duplicates from the repository root.
High-intent search queries and answers about installing and using this skill.
You can identify duplicate TCR records in a VDJdb database by running a Python-based consistency check that categorizes duplicates across resolution levels and publication sources to ensure data accuracy.
A VDJdb consistency check evaluates TCR database records to detect duplicate sequences, verify author overlap across publications, and report multi-MHC epitopes presented by inconsistent allele resolutions.
Yes, you need pandas, numpy, and scipy installed in your Python environment to process the VDJdb database files and execute the associated metadata checks for duplicate TCR detection.
You detect multi-MHC epitopes and author overlap by analyzing VDJdb metadata with Python scripts that flag epitopes presented by multiple distinct MHC molecules and evaluate shared publication authors.
Spurious high-frequency TCR records often result from duplicated entries across multiple publication sources; auditing scripts can flag these high-frequency records to help resolve data integrity issues.
Yes, you can use Python to audit VDJdb files and generate reports highlighting epitopes presented by multiple distinct MHC molecules or those with inconsistent allele resolution levels.
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